[1]胡保华,朱宗俊,穆景颂,等.基于C-FFuzzyEn的神经电生理信号同步性分析[J].中国医学物理学杂志,2023,40(5):589-594.[doi:DOI:10.3969/j.issn.1005-202X.2023.05.011]
　HU Baohua,ZHU Zongjun,MU Jingsong,et al.Neural electrophysiological signal synchronization analysis using C-FFuzzyEn[J].Chinese Journal of Medical Physics,2023,40(5):589-594.[doi:DOI:10.3969/j.issn.1005-202X.2023.05.011]
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基于C-FFuzzyEn的神经电生理信号同步性分析()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
40卷
期数:
2023年第5期
页码:
589-594
栏目:
医学信号处理与医学仪器
出版日期:
2023-05-26

文章信息/Info

Title:
Neural electrophysiological signal synchronization analysis using C-FFuzzyEn
文章编号:
1005-202X（2023）05-0589-06
作者:
胡保华1; 朱宗俊2; 穆景颂3; 金飞翔1; 鲁翠萍1; 王勇4
1.合肥学院先进制造工程学院， 安徽 合肥 230601； 2.安徽中医药大学第一附属医院针灸康复科， 安徽 合肥 230031； 3.中国科学技术大学第一附属医院康复医学科， 安徽 合肥 230001； 4.合肥工业大学机械工程学院， 安徽 合肥 230009
Author(s):
HU Baohua1;  ZHU Zongjun2;  MU Jingsong3;  JIN Feixiang1;  LU Cuiping1;  WANG Yong4
1. School of Advanced Manufacturing Engineering, Hefei University, Hefei 230601, China 2. Department of Acupuncture and Rehabilitation, the First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, China 3. Department of Rehabilitation Medicine, the First Affiliated Hospital of University of Science and Technology of China, Hefei 230001, China 4. School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China
关键词:
癫痫; 分数阶互模糊熵; 电生理信号; 同步性
Keywords:
Keywords: seizure cross fractional fuzzy entropy electrophysiological signal synchronization
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2023.05.011
文献标志码:
A
摘要:
基于传统互模糊熵，结合分数阶微积分提出分数阶互模糊熵（C-FFuzzyEn），并基于该算法分析混沌耦合系统的同步性，进行健康对照者和癫痫患者不同脑区脑电信号的耦合性对比。结果表明，与传统互模糊熵相比，C-FFuzzyEn提高了不同耦合度模型的区分能力；与健康对照者相比，癫痫患者在癫痫发作时不同通道脑电信号之间C-FFuzzyEn较小，与癫痫发作时各神经元同步放电现象相吻合；相比互模糊熵，C-FFuzzyEn区分健康对照者与癫痫患者脑区之间脑电信号同步性的效果更好。C-FFuzzyEn可应用于脑电信号等神经电生理信号的同步性分析。
Abstract:
Based on cross fuzzy entropy (C-FuzzyEn) and fractional calculus, cross fractional fuzzy entropy (C-FFuzzyEn) is proposed for analyzing the synchronization of coupled chaotic system and comparing the changes of EEG signal synchronization in healthy controls and epileptic patients. The results demonstrate that C-FFuzzyEn is superior to C-FuzzyEn in distinguishing models of different coupling degrees. In addition, compared with healthy controls, patients with epilepsy has lower C-FFuzzyEn during seizure activity, which is consistent with the synchronous firing of neurons during epileptic seizures. C-FFuzzyEn is better than C-FuzzyEn at distinguishing the synchronicity of EEG signals between brain regions in healthy controls and epileptic patients. C-FFuzzyEn can be used to analyze the synchronization of neural electrophysiological signals such as EEG signals.

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备注/Memo

备注/Memo:
【收稿日期】2023-01-14 【基金项目】国家自然科学基金（U1713210）；安徽省科技重大专项（202103a07020009）；合肥学院人才科研基金（21-22RC01） 【作者简介】胡保华，博士，讲师，研究方向：生物医学信号处理，E-mail: hanyu19900205@126.com 【通信作者】王勇，博士，教授，研究方向：生物医学信号处理，E-mail: simenkouwang@sina.com
更新日期/Last Update: 2023-05-26